In a case of generally used cameras having a small field of view, a radiative lens distortion may be mostly insignificant. However, in a case of a fisheye lens having a broad field of view, distortion related issues may occur. Since an image input through the lens may not express therein real space linearity, an issue may occur in extraction of a feature of an object from the image and recognition and classification, in addition to an issue in terms of visibility.
To solve such issues, numerous researchers have suggested distortion correcting models. The distortion correction models may be broadly classified into two models, a polynomial model and a non-polynomial model.
Although the polynomial model using several correction coefficients may be applicable to various lens distortion factors, predicting a correction coefficient for correcting a distortion may not be readily performed. Although the non-polynomial model may be a simple distortion correcting method using one or two coefficients, the non-polynomial model may not be readily applicable to a hardware operation because estimation functions such as a logarithm and a tangent are used.
In general, a vehicle is equipped with a camera configured to provide a driver with front and rear images to improve safety and convenience for the driver. Such images may provide a visual field that deviates from a visual field of the driver, and thus prevent a sudden accident. Here, a fisheye lens having a broad field of view may be used for the camera provided in the vehicle. However, as described in the foregoing, an image input through the fisheye lens may be distorted, and thus technology for correcting a distortion in real time may be needed.
A radiative distortion that may occur from an actually used fisheye lens may not be corrected using an ideally modeled non-polynomial function. Thus, in such a case, the polynomial model may be generally used to correct a distortion. However, through such a method using the polynomial model, a correction coefficient may not be readily inferred due to numerous correction coefficients, and a degree limit may occur due to an increase in an amount of calculation such as multiplication and addition when implementing an algorithm through hardware.
A distortion of an image input from a camera provided in a vehicle may be corrected based on a location of the camera, an occlusion by a vehicle bumper and a surrounding environment, and an object, for example, a front side and a rear side of the vehicle. However, since an existing algorithm and hardware module configured to correct a distortion may use several correction coefficients, infer a correction coefficient through software, and upload corresponding data, thus a distortion correcting task may not be performed in real time.
Also, in a general method of correcting a distortion, a disconnection may occur in conversion between images due to fixed correction coefficients, when expressing a corrected image in which a distortion is corrected as a plurality of images suitable to situations.